EURO 2024 Copenhagen
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3116. Data-driven integer programming models for installation of offshore wind turbines.

Invited abstract in session MA-29: Combinatorial Optimization models and applications in Logistics and Transportation I, stream Combinatorial Optimization.

Monday, 8:30-10:00
Room: 157 (building: 208)

Authors (first author is the speaker)

1. Charles Emeka Onyi
Management Science, University of Strathclyde
2. Mahdi Doostmohammadi
Management Science, University of Strathclyde
3. Kerem Akartunali
Management Science, University of Strathclyde

Abstract

Millions of pounds are involved in the construction of offshore wind turbines. Therefore, there is a need to optimize the whole process to reduce the cost and duration of the final procedure involved in wind energy generation. Specifically, this project focuses on modeling the procedure for the installation of offshore wind turbines as a mixed integer linear programming and the use of exact methods to solve those models. The objective is to minimize the total cost used in the installation procedure. To obtain an optimal solution, we devise a shortest path-like formulation using strong multicommodity flow models of the network. We show that this new formulation is NP-Hard. We propose a polyhedral analysis of the set of solutions by identifying novel problem-specific valid inequalities required to characterize the convex hull of feasible solutions. Also, we design an efficient cutting plane algorithm that identifies the optimal configuration of vessel schedules that minimizes the installation duration and cost. We present preliminary computational results on the problem specific and the literature instances that are related to the problem formulation. Also, computational instances will be tested by real-world data collected from offshore wind farm installations.

Keywords

Status: accepted

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